Efficiently supporting the existence of long trains in a generation managed by the train algorithm

ABSTRACT

A garbage collector that divides a dynamically allocated heap into car sections grouped into trains in accordance with the train algorithm subdivides large trains into subtrains. When an object that is reachable from the train-algorithm-managed generation of the heap is evacuated from a car being collected during a collection increment, it is placed into the last car in the subtrain in which the reference to it resides, even if that car is not the last car in the train to which the reference&#39;s subtrain belongs. The train-algorithm test for dead trains is performed not only on top-level trains but also on sub-trains.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention is directed to memory management. It particularlyconcerns what has come to be known as “garbage collection.”

2. Background Information

In the field of computer systems, considerable effort has been expendedon the task of allocating memory to data objects. For the purposes ofthis discussion, the term object refers to a data structure representedin a computer system's memory. Other terms sometimes used for the sameconcept are record and structure. An object may be identified by areference, a relatively small amount of information that can be used toaccess the object. A reference can be represented as a “pointer” or a“machine address,” which may require, for instance, only sixteen,thirty-two, or sixty-four bits of information, although there are otherways to represent a reference.

In some systems, which are usually known as “object oriented,” objectsmay have is associated methods, which are routines that can be invokedby reference to the object. They also may belong to a class, which is anorganizational entity that may contain method code or other informationshared by all objects belonging to that class. In the discussion thatfollows, though, the term object will not be limited to such structures;it will additionally include structures with which methods and classesare not associated.

The invention to be described below is applicable to systems thatallocate memory to objects dynamically. Not all systems employ dynamicallocation. In some computer languages, source programs must be sowritten that all objects to which the program's variables refer arebound to storage locations at compile time. This storage-allocationapproach, sometimes referred to as “static allocation,” is the policytraditionally used by the Fortran programming language, for example.

Even for compilers that are thought of as allocating objects onlystatically, of course, there is often a certain level of abstraction tothis binding of objects to storage locations. Consider the typicalcomputer system 10 depicted in FIG. 1, for example. Data, andinstructions for operating on them, that a microprocessor 11 uses mayreside in on-board cache memory or be received from further cache memory12, possibly through the mediation of a cache controller 13. Thatcontroller 13 can in turn receive such data from system read/writememory (“RAM”) 14 through a RAM controller 15 or from various peripheraldevices through a system bus 16. The memory space made available to anapplication program may be “virtual” in the sense that it may actuallybe considerably larger than RAM 14 provides. So the RAM contents will beswapped to and from a system disk 17.

Additionally, the actual physical operations performed to access some ofthe most-recently visited parts of the process's address space oftenwill actually be performed in the cache 12 or in a cache on boardmicroprocessor 11 rather than on the RAM 14, with which those cachesswap data and instructions just as RAM 14 and system disk 17 do witheach other.

A further level of abstraction results from the fact that an applicationwill often be run as one of many processes operating concurrently withthe support of an underlying operating system. As part of that system'smemory management, the application's memory space may be moved amongdifferent actual physical locations many times in order to allowdifferent processes to employ shared physical memory devices. That is,the location specified in the application's machine code may actuallyresult in different physical locations at different times because theoperating system adds different offsets to themachine-language-specified location.

Despite these expedients, the use of static memory allocation in writingcertain long-lived applications makes it difficult to restrict storagerequirements to the available memory space. Abiding by space limitationsis easier when the platform provides for dynamic memory allocation,i.e., when memory space to be allocated to a given object is determinedonly at run time.

Dynamic allocation has a number of advantages, among which is that therun-time system is able to adapt allocation to run-time conditions. Forexample, the programmer can specify that space should be allocated for agiven object only in response to a particular run-time condition. TheC-language library function malloc( ) is often used for this purpose.Conversely, the programmer can specify conditions under which memorypreviously allocated to a given object can be reclaimed for reuse. TheC-language library function free( ) results in such memory reclamation.

Because dynamic allocation provides for memory reuse, it facilitatesgeneration of large or long-lived applications, which over the course oftheir lifetimes may employ objects whose total memory requirements wouldgreatly exceed the available memory resources if they were bound tomemory locations statically.

Particularly for long-lived applications, though, allocation andreclamation of dynamic memory must be performed carefully. If theapplication fails to reclaim unused memory—or, worse, loses track of theaddress of a dynamically allocated segment of memory—its memoryrequirements will grow over time to exceed the system's availablememory. This kind of error is known as a “memory leak.”

Another kind of error occurs when an application reclaims memory forreuse even though it still maintains a reference to that memory. If thereclaimed memory is reallocated for a different purpose, the applicationmay inadvertently manipulate the same memory in multiple inconsistentways. This kind of error is known as a “dangling reference,” because anapplication should not retain a reference to a memory location once thatlocation is reclaimed. Explicit dynamic-memory management by usinginterfaces like malloc( )/free( ) often leads to these problems.

A way of reducing the likelihood of such leaks and related errors is toprovide memory-space reclamation in a more-automatic manner. Techniquesused by systems that reclaim memory space automatically are commonlyreferred to as “garbage collection.” Garbage collectors operate byreclaiming space that they no longer consider “reachable.” Staticallyallocated objects represented by a program's global variables arenormally considered reachable throughout a program's life. Such objectsare not ordinarily stored in the garbage collector's managed memoryspace, but they may contain references to dynamically allocated objectsthat are, and such objects are considered reachable. Clearly, an objectreferred to in the processor's call stack is reachable, as is an objectreferred to by register contents. And an object referred to by anyreachable object is also reachable.

The use of garbage collectors is advantageous because, whereas aprogrammer working on a particular sequence of code can perform his taskcreditably in most respects with only local knowledge of the applicationat any given time, memory allocation and reclamation require a globalknowledge of the program. Specifically, a programmer dealing with agiven sequence of code does tend to know whether some portion of memoryis still in use for that sequence of code, but it is considerably moredifficult for him to know what the rest of the application is doing withthat memory. By tracing references from some conservative notion of a“root set,” e.g., global variables, registers, and the call stack,automatic garbage collectors obtain global knowledge in a methodicalway. By using a garbage collector, the programmer is relieved of theneed to worry about the application's global state and can concentrateon local-state issues, which are more manageable. The result isapplications that are more robust, having no dangling references andfewer memory leaks.

Garbage-collection mechanisms can be implemented by various parts andlevels of a computing system. One approach is simply to provide them aspart of a batch compiler's output. Consider FIG. 2's simplebatch-compiler operation, for example. A computer system executes inaccordance with compiler object code and therefore acts as a compiler20. The compiler object code is typically stored on a medium such asFIG. 1's system disk 17 or some other machine-readable medium, and it isloaded into RAM 14 to configure the computer system to act as acompiler. In some cases, though, the compiler object code's persistentstorage may instead be provided in a server system remote from themachine that performs the compiling. The electrical signals that carrythe digital data by which the computer systems exchange that code areexamples of the kinds of electromagnetic signals by which the computerinstructions can be communicated. Others are radio waves, microwaves,and both visible and invisible light.

The input to the compiler is the application source code, and the endproduct of the compiler process is application object code. This objectcode defines an application 21, which typically operates on input suchas mouse clicks, etc., to generate a display or some other type ofoutput. This object code implements the relationship that the programmerintends to specify by his application source code. In one approach togarbage collection, the compiler 20, without the programmer's explicitdirection, additionally generates code that automatically reclaimsunreachable memory space.

Even in this simple case, though, there is a sense in which theapplication does not itself provide the entire garbage collector.Specifically, the application will typically call upon the underlyingoperating system's memory-allocation functions. And the operating systemmay in turn take advantage of various hardware that lends itselfparticularly to use in garbage collection. So even a very simple systemmay disperse the garbage-collection mechanism over a number ofcomputer-system layers.

To get some sense of the variety of system components that can be usedto implement garbage collection, consider FIG. 3's example of a morecomplex way in which various levels of source code can result in themachine instructions that a processor executes. In the FIG. 3arrangement, the human applications programmer produces source code 22written in a high-level language. A compiler 23 typically converts thatcode into “class files.” These files include routines written ininstructions, called “byte codes” 24, for a “virtual machine” thatvarious processors can be software-configured to emulate. Thisconversion into byte codes is almost always separated in time from thosecodes' execution, so FIG. 3 divides the sequence into a “compile-timeenvironment” 25 separate from a “run-time environment” 26, in whichexecution occurs. One example of a high-level language for whichcompilers are available to produce such virtual-machine instructions isthe Java™ programming language. (Java is a trademark or registeredtrademark of Sun Microsystems, Inc., in the United States and othercountries.)

Most typically, the class files' byte-code routines are executed by aprocessor under control of a virtual-machine process 27. That processemulates a virtual machine from whose instruction set the byte codes aredrawn. As is true of the compiler 23, the virtual-machine process 27 maybe specified by code stored on a local disk or some othermachine-readable medium from which it is read into FIG. 1's RAM 14 toconfigure the computer system to implement the garbage collector andotherwise act as a virtual machine. Again, though, that code'spersistent storage may instead be provided by a server system remotefrom the processor that implements the virtual machine, in which casethe code would be transmitted electrically or optically to thevirtual-machine-implementing processor.

In some implementations, much of the virtual machine's action inexecuting these byte codes is most like what those skilled in the artrefer to as “interpreting,” so FIG. 3 depicts the virtual machine asincluding an “interpreter” 28 for that purpose. In addition to orinstead of running an interpreter, many virtual-machine implementationsactually is compile the byte codes concurrently with the resultantobject code's execution, so FIG. 3 depicts the virtual machine asadditionally including a “just-in-time” compiler 29. The arrangement ofFIG. 3 differs from FIG. 2 in that the compiler 23 for converting thehuman programmer's code does not contribute to providing thegarbage-collection function; that results largely from the virtualmachine 27's operation.

Those skilled in that art will recognize that both of theseorganizations are merely exemplary, and many modem systems employ hybridmechanisms, which partake of the characteristics of traditionalcompilers and traditional interpreters both. The invention to bedescribed below is applicable independently of whether a batch compiler,a just-in-time compiler, an interpreter, or some hybrid is employed toprocess source code. In the remainder of this application, therefore, wewill use the term compiler to refer to any such mechanism, even if it iswhat would more typically be called an interpreter.

The arrangement of FIG. 3 differs from FIG. 2 in that the compiler 23for converting the human programmer's code does not contribute toproviding the garbage-collection function; that results largely from thevirtual machine 27's operation. Although though the FIG. 3 arrangementis a popular one, it is by no means universal, and many furtherimplementation types can be expected. Proposals have even been made toimplement the virtual machine 27's behavior in a hardware processor, inwhich case the hardware itself would provide some or all of thegarbage-collection function.

In short, garbage collectors can be implemented in a wide range ofcombinations of hardware and/or software. As is true of most of thegarbage-collection techniques described in the literature, the inventionto be described below is applicable to most such systems.

By implementing garbage collection, a computer system can greatly reducethe occurrence of memory leaks and other software deficiencies in whichhuman programming frequently results. But it can also have significantadverse performance effects if it is not implemented carefully. Todistinguish the part of the program that does “useful” work from thatwhich does the garbage collection, the term mutator is sometimes used indiscussions of these effects; from the collector's point of view, whatthe mutator does is mutate active data structures' connectivity.

Some garbage-collection approaches rely heavily on interleavinggarbage-collection steps among mutator steps. In one type ofgarbage-collection approach, for instance, the mutator operation ofwriting a reference is followed immediately by garbage-collector stepsused to maintain a reference count in that object's header, and code forsubsequent new-object storage includes steps for finding space occupiedby objects whose reference count has fallen to zero. Obviously, such anapproach can slow mutator operation significantly.

Other approaches therefore interleave very few garbage-collector-relatedinstructions into the main mutator process but instead interrupt it fromtime to time to perform garbage-collection cycles, in which the garbagecollector finds unreachable objects and reclaims their memory space forreuse. Such an approach will be assumed in discussing FIG. 4's depictionof a simple garbage-collection operation. Within the memory spaceallocated to a given application is a part 40 managed by automaticgarbage collection. In the following discussion, this will be referredto as the “heap,” although in other contexts that term refers to alldynamically allocated memory. During the course of the application'sexecution, space is allocated for various objects 42, 44, 46, 48, and50. Typically, the mutator allocates space within the heap by invokingthe garbage collector, which at some level manages access to the heap.Basically, the mutator asks the garbage collector for a pointer to aheap region where it can safely place the object's data. The garbagecollector keeps track of the fact that the thus-allocated region isoccupied. It will refrain from allocating that region in response to anyother request until it determines that the mutator no longer needs theregion allocated to that object.

Garbage collectors vary as to which objects they consider reachable andunreachable able. For the present discussion, though, an object will beconsidered “reachable” if it is referred to, as object 42 is, by areference in the root set 52. The root set consists of reference valuesstored in the mutator's threads' call stacks, the CPU registers, andglobal variables outside the garbage-collected heap. An object is alsoreachable if it is referred to, as object 46 is, by another reachableobject (in this case, object 42). Objects that are not reachable can nolonger affect the program, so it is safe to re-allocate the memoryspaces that they occupy.

A typical approach to garbage collection is therefore to identify allreachable objects and reclaim any previously allocated memory that thereachable objects do not occupy. A typical garbage collector mayidentify reachable objects by tracing references from the root set 52.For the sake of simplicity, FIG. 4 depicts only one reference from theroot set 52 into the heap 40. (Those skilled in the art will recognizethat there are many ways to identify references, or at least datacontents that may be references.) The collector notes that the root setpoints to object 42, which is therefore reachable, and that reachableobject 42 points to object 46, which therefore is also reachable. Butthose reachable objects point to no other objects, so objects 44, 48,and 50 are all unreachable, and their memory space may be reclaimed.This may involve, say, placing that memory space in a list of freememory blocks.

To avoid excessive heap fragmentation, some garbage collectorsadditionally relocate reachable objects. FIG. 5 shows a typicalapproach. The heap is partitioned into two halves, hereafter called“semi-spaces.” For one garbage-collection cycle, all objects areallocated in one semi-space 54, leaving the other semi-space 56 free.When the garbage-collection cycle occurs, objects identified asreachable are “evacuated” to the other semi-space 56, so all ofsemi-space 54 is then considered free. Once the garbage-collection cyclehas occurred, all new objects are allocated in the lower semi-space 56until yet another garbage-collection cycle occurs, at which time thereachable objects are evacuated back to the upper semi-space 54.

Although this relocation requires the extra steps of copying thereachable objects and updating references to them, it tends to be quiteefficient, since most new objects quickly become unreachable, so most ofthe current semi-space is actually garbage. That is, only a relativelyfew, reachable objects need to be relocated, after which the entiresemi-space contains only garbage and can be pronounced free forreallocation.

Now, a collection cycle can involve following all reference chains fromthe basic root set—i.e., from inherently reachable locations such as thecall stacks, class statics and other global variables, and registers—andreclaiming all space occupied by objects not encountered in the process.And the simplest way of performing such a cycle is to interrupt themutator to provide a collector interval in which the entire cycle isperformed before the mutator resumes. For certain types of applications,this approach to collection-cycle scheduling is acceptable and, in fact,highly efficient.

For many interactive and real-time applications, though, this approachis not acceptable. The delay in mutator operation that the collectioncycle's execution causes can be annoying to a user and can prevent areal-time application from responding to its environment with therequired speed. In some applications, choosing collection timesopportunistically can reduce this effect. Collection intervals can beinserted when an interactive mutator reaches a point at which it awaitsuser input, for instance.

So it may often be true that the garbage-collection operation's effecton performance can depend less on the total collection time than on whencollections actually occur. But another factor that often is even moredeterminative is the duration of any single collection interval, i.e.,how long the mutator must remain quiescent at any one time. In aninteractive system, for instance, a user may never noticehundred-millisecond interruptions for garbage collection, whereas mostusers would find interruptions lasting for two seconds to be annoying.

The cycle may therefore be divided up among a plurality of collectorintervals. When a collection cycle is divided up among a plurality ofcollection intervals, it is only after a number of intervals that thecollector will have followed all reference chains and be able toidentify as garbage any objects not thereby reached. This approach ismore complex than completing the cycle in a single collection interval;the mutator will usually modify references between collection intervals,so the collector must repeatedly update its view of the reference graphin the midst of the collection cycle. To make such updates practical,the mutator must communicate with the collector to let it know whatreference changes are made between intervals.

An even more complex approach, which some systems use to eliminatediscrete pauses or maximize resource-use efficiency, is to execute themutator and collector in concurrent execution threads. Most systems thatuse this approach use it for most but not all of the collection cycle;the mutator is usually interrupted for a short collector interval, inwhich a part of the collector cycle takes place without mutation.

Independent of whether the collection cycle is performed concurrentlywith mutator operation, is completed in a single interval, or extendsover multiple intervals is the question of whether the cycle iscomplete, as has tacitly been assumed so far, or is instead“incremental.” In incremental collection, a collection cycle constitutesonly an increment of collection: the collector does not follow allreference chains from the basic root set completely. Instead, itconcentrates on only a portion, or collection set, of the heap.Specifically, it identifies every collection-set object referred to by areference chain that extends into the collection set from outside of it,and it reclaims the collection-set space not occupied by such objects,possibly after evacuating them from the collection set.

By thus culling objects referenced by reference chains that do notnecessarily originate in the basic root set, the collector can bethought of as expanding the root set to include some locations that maynot be reachable as additional roots. Although incremental collectionthereby leaves “floating garbage,” it can result in relatively low pausetimes even if entire collection increments are completed duringrespective single collection intervals.

Most collectors that employ incremental collection operate in“generations,” although this is not necessary in principle. Differentportions, or generations, of the heap are subject to differentcollection policies. New objects are allocated in a “young” generation,and older objects are promoted from younger generations to older or more“mature” generations. Collecting the younger generations more frequentlythan the others yields greater efficiency because the youngergenerations tend to accumulate garbage faster; newly allocated objectstend to “die,” while older objects tend to “survive.”

But generational collection effectively increases the root set for agiven generation. Consider FIG. 6, which depicts a heap as organizedinto three generations 58, 60, and 62. Assume that generation 60 is tobe collected. The process for this individual generation may be more orless the same as that described in connection with FIGS. 4 and 5 for theentire heap, with one major exception. In the case of a singlegeneration, the root set must be considered to include not only the callstack, registers, and global variables represented by set 52 but alsoobjects in the other generations 58 and 62, which themselves may containreferences to objects in generation 60. So pointers must be traced notonly from the basic root set 52 but also from objects within the othergenerations.

One could perform this tracing by simply inspecting all references inall other generations at the beginning of every collection interval, andit turns out that this approach is actually feasible in some situations.But it takes too long in other situations, so workers in this field haveemployed a number of approaches to expediting reference tracing. Oneapproach is to include so-called write barriers in the mutator process.A write barrier is code added to a write operation to record informationfrom which the collector can determine where references were written ormay have been since the last collection interval. A reference list canthen be maintained by taking such a list as it existed at the end of theprevious collection interval and updating it by inspecting onlylocations identified by the write barrier as possibly modified since thelast collection interval.

One of the many write-barrier implementations commonly used by workersin this art employs what has been referred to as the “card table.” FIG.6 depicts the various generations as being divided into smallersections, known for this purpose as “cards.” Card tables 64, 66, and 68associated with respective generations contain an entry for each oftheir cards. When the mutator writes a reference in a card, it makes anappropriate entry in the card-table location associated with that card(or, say, with the card in which the object containing the referencebegins). Most write-barrier implementations simply make a Boolean entryindicating that the write operation has been performed, although somemay be more elaborate. The mutator having thus left a record of wherenew or modified references may be, the collector can thereafter prepareappropriate summaries of that information, as will be explained in duecourse. For the sake of concreteness, we will assume that the summariesare maintained by steps that occur principally at the beginning of eachcollection interval.

Of course, there are other write-barrier approaches, such as simplyhaving the write barrier add to a list of addresses where referenceswhere written. Also, although there is no reason in principle to favorany particular number of generations, and although FIG. 6 shows three,most generational garbage collectors have only two generations, of whichone is the young generation and the other is the mature generation.Moreover, although FIG. 6 shows the generations as being of the samesize, a more-typical configuration is for the young generation to beconsiderably smaller. Finally, although we assumed for the sake ofsimplicity that collection during a given interval was limited to onlyone generation, a more-typical approach is actually to collect the wholeyoung generation at every interval but to collect the mature one lessfrequently.

Some collectors collect the entire young generation in every intervaland may thereafter perform mature-generation collection in the sameinterval. It may therefore take relatively little time to scan allyoung-generation objects remaining after young-generation collection tofind references into the mature generation. Even when such collectors douse card tables, therefore, they often do not use them for findingyoung-generation references that refer to mature-generation objects. Onthe other hand, laboriously scanning the entire mature generation forreferences to young-generation (or mature-generation) objects wouldordinarily take too long, so the collector uses the card table to limitthe amount of memory it searches for mature-generation references.

Now, although it typically takes very little time to collect the younggeneration, it may take more time than is acceptable within a singlegarbage-collection cycle to collect the entire mature generation. Sosome garbage collectors may collect the mature generation incrementally;that is, they may perform only a part of the mature generation'scollection during any particular collection cycle. Incrementalcollection presents the problem that, since the generation's unreachableobjects outside the “collection set” of objects processed during thatcycle cannot be recognized as unreachable, collection-set objects towhich they refer tend not to be, either.

To reduce the adverse effect this would otherwise have on collectionefficiency, workers in this field have employed the “train algorithm,”which FIG. 7 depicts. A generation to be collected incrementally isdivided into sections, which for reasons about to be described arereferred to as “car sections.” Conventionally, a generation'sincremental collection occurs in fixed-size sections, and a carsection's size is that of the generation portion to be collected duringone cycle.

The discussion that follows will occasionally employ the nomenclature inthe literature by using the term car instead of car section. But theliterature seems to use that term to refer variously not only to memorysections themselves but also to data structures that the train algorithmemploys to manage them when they contain objects, as well as to themore-abstract concept that the car section and managing data structurerepresent in discussions of the algorithm. So the following discussionwill more frequently use the expression car section to emphasize theactual sections of memory space for whose management the car concept isemployed.

According to the train algorithm, the car sections are grouped into“trains,” which are ordered, conventionally according to age. Forexample, FIG. 7 shows an oldest train 73 consisting of a generation 74'sthree car sections described by associated data structures 75, 76, and78, while a second train 80 consists only of a single car section,represented by structure 82, and the youngest train 84 (referred to asthe “allocation train”) consists of car sections that data structures 86and 88 represent. As will be seen below, car sections' train membershipscan change, and any car section added to a train is typically added tothe end of a train.

Conventionally, the car collected in an increment is the one addedearliest to the oldest train, which in this case is car 75. All of thegeneration's cars can thus be thought of as waiting for collection in asingle long line, in which cars are ordered in accordance with the orderof the trains to which they belong and, within trains, in accordancewith the order in which they were added to those trains.

As is usual, the way in which reachable objects are identified is todetermine whether there are references to them in the root set or in anyother object already determined to be reachable. In accordance with thetrain algorithm, the collector additionally performs a test to determinewhether there are any references at all from outside the oldest train toobjects within it. If there are not, then all cars within the train canbe reclaimed, even though not all of those cars are in the collectionset. And the train algorithm so operates that inter-car references tendto be grouped into trains, as will now be explained.

To identify references into the car from outside of it, train-algorithmimplementations typically employ “remembered sets.” As card tables are,remembered sets are used to keep track of references. Whereas acard-table entry contains information about references that theassociated card contains, though, a remembered set associated with agiven region contains information about references into that region fromlocations outside of it. In the case of the train algorithm, rememberedsets are associated with car sections. Each remembered set, such as car75's remembered set 90, lists locations in the generation that containreferences into the associated car section.

The remembered sets for all of a generation's cars are typically updatedat the start of each collection cycle. To illustrate how such updatingand other collection operations may be carried out, FIGS. 8A and 8B(together, “FIG. 8”) depict an operational sequence in a system of thetypical type mentioned above. That is, it shows a sequence of operationsthat may occur in a system in which the entire garbage-collected heap isdivided into two generations, namely, a young generation and an oldgeneration, and in which the young generation is much smaller than theold generation. FIG. 8 is also based on the assumption and that thetrain algorithm is used only for collecting the old generation.

Block 102 represents a period of the mutator's operation. As wasexplained above, the mutator makes a card-table entry to identify anycard that it has “dirtied” by adding or modifying a reference that thecard contains. At some point, the mutator will be interrupted forcollector operation. Different implementations employ different eventsto trigger such an interruption, but we will assume for the sake ofconcreteness that the system's dynamic-allocation routine causes suchinterruptions when no room is left in the young generation for anyfurther allocation. A dashed line 103 represents the transition frommutator operation and collector operation.

In the system assumed for the FIG. 8 example, the collector collects the(entire) young generation each time such an interruption occurs. Whenthe young generation's collection ends, the mutator operation usuallyresumes, without the collector's having collected any part of the oldgeneration. Once in a while, though, the collector also collects part ofthe old generation, and FIG. 8 is intended to illustrate such anoccasion.

When the collector's interval first starts, it first processes the cardtable, in an operation that block 104 represents. As was mentionedabove, the collector scans the “dirtied” cards for references into theyoung generation. If a reference is found, that fact is memorializedappropriately. If the reference refers to a young-generation object, forexample, an expanded card table may be used for this purpose. For eachcard, such an expanded card table might include a multi-byte array usedto summarize the card's reference contents. The summary may, forinstance, be a list of offsets that indicate the exact locations withinthe card of references to young-generation objects, or it may be a listof fine-granularity “sub-cards” within which references toyoung-generation objects may be found. If the reference refers to anold-generation object, the collector often adds an entry to theremembered set associated with the car containing that old-generationobject. The entry identifies the reference's location, or at least asmall region in which the reference can be found. For reasons that willbecome apparent, though, the collector will typically not bother toplace in the remembered set the locations of references from objects incar sections farther forward in the collection queue than thereferred-to object, i.e., from objects in older trains or in cars addedearlier to the same train.

The collector then collects the young generation, as block 105indicates. (Actually, young-generation collection may be interleavedwith the dirty-region scanning, but the drawing illustrates it forpurpose; of explanation as being separate.) If a young-generation objectis referred to by a reference that card-table scanning has revealed,that object is considered to be potentially reachable, as is anyyoung-generation object referred to by a reference in the root set or inanother reachable young-generation object. The space occupied by anyyoung-generation object thus considered reachable is withheld fromreclamation. For example, a young-generation object may be evacuated toa young-generation semi-space that will be used for allocation duringthe next mutator interval. It may instead be promoted into the oldergeneration, where it is placed into a car containing a reference to itor into a car in the last train. Or some other technique may be used tokeep the memory space it occupies off the system's free list. Thecollector then reclaims any young-generation space occupied by any otherobjects, i.e., by any young-generation objects not identified astransitively reachable through references located outside the younggeneration.

The collector then performs the train algorithm's central test, referredto above, of determining whether there are any references into theoldest train from outside of it. As was mentioned above, the actualprocess of determining, for each object, whether it can be identified asunreachable is performed for only a single car section in any cycle. Inthe absence of features such as those provided by the train algorithm,this would present a problem, because garbage structures may be largerthan a car section. Objects in such structures would therefore(erroneously) appear reachable, since they are referred to from outsidethe car section under consideration. But the train algorithmadditionally keeps track of whether there are any references into agiven car from outside the train to which it belongs, and trains' sizesare not limited. As will be apparent presently, objects not found to beunreachable are relocated in such a way that garbage structures tend tobe gathered into respective trains into which, eventually, no referencesfrom outside the train point. If no references from outside the trainpoint to any objects inside the train, the train can be recognized ascontaining only garbage. This is the test that block 106 represents. Allcars in a train thus identified as containing only garbage can bereclaimed.

The question of whether old-generation references point into the trainfrom outside of it is (conservatively) answered in the course ofupdating remembered sets; in the course of updating a car's rememberedset, it is a simple matter to flag the car as being referred to fromoutside the train. The step-106 test additionally involves determiningwhether any references from outside the old generation point into theoldest train. Various approaches to making this determination have beensuggested, including the conceptually simple approach of merelyfollowing all reference chains from the root set until those chains (1)terminate, (2) reach an old-generation object outside the oldest train,or (3) reach an object in the oldest train. In the two-generationexample, most of this work can be done readily by identifying referencesinto the collection set from live young-generation objects during theyoung-generation collection. If one or more such chains reach the oldesttrain, that train includes reachable objects. It may also includereachable objects if the remembered-set-update operation has found oneor more references into the oldest train from outside of it. Otherwise,that train contains only garbage, and the collector reclaims all of itscar sections for reuse, as block 107 indicates. The collector may thenreturn control to the mutator, which resumes execution, as FIG. 8B'sblock 108 indicates.

If the train contains reachable objects, on the other hand, thecollector turns to evacuating potentially reachable objects from thecollection set. The first operation, which block 110 represents, is toremove from the collection set any object that is reachable from theroot set by way of a reference chain that does not pass through the partof the old generation that is outside of the collection set. In theillustrated arrangement, in which there are only two generations, andthe young generation has previously been completely collected during thesame interval, this means evacuating from a collection set any objectthat (1) is directly referred to by a reference in the root set, (2) isdirectly referred to by a reference in the young generation (in which noremaining objects have been found unreachable), or (3) is referred to byany reference in an object thereby evacuated. All of the objects thusevacuated are placed in cars in the youngest train, which was newlycreated during the collection cycle. Certain of the mechanics involvedin the evacuation process are described in more detail in connectionwith similar evacuation performed, as blocks 112 and 114 indicate, inresponse to remembered-set entries.

FIG. 9 illustrates how the processing represented by block 114 proceeds.The entries identify heap regions, and, as block 116 indicates, thecollector scans the thus-identified heap regions to find references tolocations in the collection-set. As blocks 118 and 120 indicate, thatentry's processing continues until the collector finds no more suchreferences. Every time the collector does find such a reference, itchecks to determine whether, as a result of a previous entry'sprocessing, the referred-to object has already been evacuated. If it hasnot, the collector evacuates the referred-to object to a (possibly new)car in the train containing the reference, as blocks 122 and 124indicate.

As FIG. 10 indicates, the evacuation operation includes more than justobject relocation, which block 126 represents. Once the object has beenmoved, the collector places a forwarding pointer in the collection-setlocation from which it was evacuated, for a purpose that will becomeapparent presently. Block 128 represents that step. (Actually, there aresome cases in which the evacuation is only a “logical” evacuation: thecar containing the object is simply re-linked to a different logicalplace in the collection sequence, but its address does not change. Insuch cases, forwarding pointers are unnecessary.) Additionally, thereference in response to which the object was evacuated is updated topoint to the evacuated object's new location, as block 130 indicates.And, as block 132 indicates, any reference contained in the evacuatedobject is processed, in an operation that FIGS. 11A and 11B (together,“FIG. 11”) depict.

For each one of the evacuated object's references, the collector checksto see whether the location that it refers to is in the collection set.As blocks 134 and 136 indicate, the reference processing continues untilall references in the evacuated object have been processed. In themeantime, if a reference refers to a collection-set location thatcontains an object not yet evacuated, the collector evacuates thereferred-to object to the train to which the evacuated object containingthe reference was evacuated, as blocks 138 and 140 indicate.

If the reference refers to a location in the collection set from whichthe object has already been evacuated, then the collector uses theforwarding pointer left in that location to update the reference, asblock 142 indicates. Before the processing of FIG. 11, the rememberedset of the referred-to object's car will have an entry that identifiesthe evacuated object's old location as one containing a reference to thereferred-to object. But the evacuation has placed the reference in a newlocation, for which the remembered set of the referred-to object's carmay not have an entry. So, if that new location is not as far forward asthe referred-to object, the collector adds to that remembered set anentry identifying the reference's new region, as blocks 144 and 146indicate. As the drawings show, the same type of remembered-set updateis performed if the object referred to by the evacuated reference is notin the collection set.

Now, some train-algorithm implementations postpone processing of thereferences contained in evacuated collection-set objects until after alldirectly reachable collection-set objects have been evacuated. In theimplementation that FIG. 10 illustrates, though, the processing of agiven evacuated object's references occurs before the next object isevacuated. So FIG. 11's blocks 134 and 148 indicate that the FIG. 11operation is completed when all of the references contained in theevacuated object have been processed. This completes FIG. 10'sobject-evacuation operation, which FIG. 9's block 124 represents.

As FIG. 9 indicates, each collection-set object referred to by areference in a remembered-set-entry-identified location is thusevacuated if it has not been already. If the object has already beenevacuated from the referred-to location, the reference to that locationis updated to point to the location to which the object has beenevacuated. If the remembered set associated with the car containing theevacuated object's new location does not include an entry for thereference's location, it is updated to do so if the car containing thereference is younger than the car containing the evacuated object. Block150 represents updating the reference and, if necessary, the rememberedset.

As FIG. 8's blocks 112 and 114 indicate, this processing ofcollection-set remembered sets is performed initially only for entriesthat do not refer to locations in the oldest train. Those that do areprocessed only after all others have been, as blocks 152 and 154indicate.

When this process has been completed, the collection set's memory spacecan be reclaimed, as block 164 indicates, since no remaining object isreferred to from outside the collection set: any remainingcollection-set object is unreachable. The collector then relinquishescontrol to the mutator.

FIGS. 12A–12J illustrate results of using the train algorithm. FIG. 12Arepresents a generation in which objects have been allocated in nine carsections. The oldest train has four cars, numbered 1.1 through 1.4. Car1.1 has two objects, A and B. There is a reference to object B in theroot set (which, as was explained above, includes live objects in theother generations). Object A is referred to by object L, which is in thethird train's sole car section. In the generation's remembered sets 170,a reference in object L has therefore been recorded against car 1.1.

Processing always starts with the oldest train's earliest-added car, sothe garbage collector refers to car 1.1's remembered set and finds thatthere is a reference from object L into the car being processed. Itaccordingly evacuates object A to the train that object L occupies. Theobject being evacuated is often placed in one of the selected train'sexisting cars, but we will assume for present purposes that there is notenough room. So the garbage collector evacuates object A into a new carsection and updates appropriate data structures to identify it as thenext car in the third train. FIG. 12B depicts the result: a new car hasbeen added to the third train, and object A is placed in it.

FIG. 12B also shows that object B has been evacuated to a new caroutside the first train. This is because object B has an externalreference, which, like the reference to object A, is a reference fromoutside the first train, and one goal of the processing is to formtrains into which there are no further references. Note that, tomaintain a reference to the same object, object L's reference to objectA has had to be rewritten, and so have object B's reference to object Aand the inter-generational pointer to object B. In the illustratedexample, the garbage collector begins a new train for the car into whichobject B is evacuated, but this is not a necessary requirement of thetrain algorithm. That algorithm requires only that externally referencedobjects be evacuated to a newer train.

Since car 1.1 no longer contains live objects, it can be reclaimed, asFIG. 12B also indicates. Also note that the remembered set for car 2.1now includes the address of a reference in object A, whereas it did notbefore. As was stated before, remembered sets in the illustratedembodiment include only references from cars further back in the orderthan the one with which the remembered set is associated. The reason forthis is that any other cars will already be reclaimed by the time thecar associated with that remembered set is processed, so there is noreason to keep track of references from them.

The next step is to process the next car, the one whose index is 1.2.Conventionally, this would not occur until some collection cycle afterthe one during which car 1.1 is collected. For the sake of simplicity wewill assume that the mutator has not changed any references into thegeneration in the interim.

FIG. 12B depicts car 1.2 as containing only a single object, object C,and that car's remembered set contains the address of an inter-carreference from object F. The garbage collector follows that reference toobject C. Since this identifies object C as possibly reachable, thegarbage collector evacuates it from car set 1.2, which is to bereclaimed. Specifically, the garbage collector removes object C to a newcar section, section 1.5, which is linked to the train to which thereferring object F's car belongs. Of course, object F's reference needsto be updated to object C's new location. FIG. 12C depicts theevacuation's result.

FIG. 12C also indicates that car set 1.2 has been reclaimed, and car 1.3is next to be processed. The only address in car 1.3's remembered set isthat of a reference in object G. Inspection of that reference revealsthat it refers to object F. Object F may therefore be reachable, so itmust be evacuated before car section 1.3 is reclaimed. On the otherhand, there are no references to objects D and E, so they are clearlygarbage. FIG. 12D depicts the result of reclaiming car 1.3's space afterevacuating possibly reachable object F.

In the state that FIG. 12D depicts, car 1.4 is next to be processed, andits remembered set contains the addresses of references in objects K andC. Inspection of object K's reference reveals that it refers to objectH, so object H must be evacuated. Inspection of the other remembered-setentry, the reference in object C, reveals that it refers to object G, sothat object is evacuated, too. As FIG. 12E illustrates, object H must beadded to the second train, to which its referring object K belongs. Inthis case there is room enough in car 2.2, which its referring object Koccupies, so evacuation of object H does not require that object K'sreference to object H be added to car 2.2's remembered set. Object G isevacuated to a new car in the same train, since that train is wherereferring object C resides. And the address of the reference in object Gto object C is added to car 1.5's remembered set.

FIG. 12E shows that this processing has eliminated all references intothe first train, and it is an important part of the train algorithm totest for this condition. That is, even though there are references intoboth of the train's cars, those cars' contents can be recognized as allgarbage because there are no references into the train from outside ofit. So all of the first train's cars are reclaimed.

The collector accordingly processes car 2.1 during the next collectioncycle, and that car's remembered set indicates that there are tworeferences outside the car that refer to objects within it. Thosereferences are in object K, which is in the same train, and object A,which is not. Inspection of those references reveals that they refer toobjects I and J, which are evacuated.

The result, depicted in FIG. 12F, is that the remembered sets for thecars in the second train reveal no inter-car references, and there areno inter-generational references into it, either. That train's carsections therefore contain only garbage, and their memory space can bereclaimed.

So car 3.1 is processed next. Its sole object, object L, is referred tointer-generationally as well as by a reference in the fourth train'sobject M. As FIG. 12G shows, object L is therefore evacuated to thefourth train. And the address of the reference in object L to object Ais placed in the remembered set associated with car 3.2, in which objectA resides.

The next car to be processed is car 3.2, whose remembered set includesthe addresses of references into it from objects B and L. Inspection ofthe reference from object B reveals that it refers to object A, whichmust therefore be evacuated to the fifth train before car 3.2 can bereclaimed. Also, we assume that object A cannot fit in car section 5.1,so a new car 5.2 is added to that train, as FIG. 12H shows, and object Ais placed in its car section. All referred-to objects in the third trainhaving been evacuated, that (single-car) train can be reclaimed in itsentirety.

A further observation needs to be made before we leave FIG. 12G. Car3.2's remembered set additionally lists a reference in object L, so thegarbage collector inspects that reference and finds that it points tothe location previously occupied by object A. This brings up a featureof copying-collection techniques such as the typical train-algorithmimplementation. When the garbage collector evacuates an object from acar section, it marks the location as having been evacuated and leavesthe address of the object's new location. So, when the garbage collectortraces the reference from object L, it finds that object A has beenremoved, and it accordingly copies the new location into object L as thenew value of its reference to object A.

In the state that FIG. 12H illustrates, car 4.1 is the next to beprocessed. Inspection of the fourth train's remembered sets reveals nointer-train references into it, but the inter-generational scan(possibly performed with the aid of FIG. 6's card tables) revealsinter-generational references into car 4.2. So the fourth train cannotbe reclaimed yet. The garbage collector accordingly evacuates car 4.1'sreferred-to objects in the normal manner, with the result that FIG. 12Idepicts.

In that state, the next car to be processed has only inter-generationalreferences into it. So, although its referred-to objects must thereforebe evacuated from the train, they cannot be placed into trains thatcontain references to them. Conventionally, such objects are evacuatedto a train at the end of the train sequence. In the illustratedimplementation, a new train is formed for this purpose, so the result ofcar 4.2's processing is the state that FIG. 12J depicts.

Processing continues in this same fashion. Of course, subsequentcollection cycles will not in general proceed, as in the illustratedcycles, without any reference changes by the mutator and without anyaddition of further objects. But reflection reveals that the generalapproach just described still applies when such mutations occur.

In short, evacuating collection-set objects to the last cars of thetrains that contain references to them tends to collapse large garbagestructures into single trains, where their nature as garbage can berecognized, despite the incremental nature of the collection, by thefact that no references outside the train refer to objects inside it.

SUMMARY OF THE INVENTION

I have recognized that the evacuation policy can be improved in such away as to reduce the amount of evacuation work and expedite therecognition of garbage structures in large trains. In accordance withthe invention, large trains are divided into subtrains, and an objectthat is evacuated from the collection set because of a reference locatedin the train-algorithm-managed generation is not in general placed inthe last car of the train containing the reference. Instead, it isplaced in the last car of the subtrain in which the reference islocated.

This has a number of positive effects. It makes it more likely thatobjects referred to only by garbage-object references will end up in thesame collection set as the references to them and will thereby berecognized as garbage. This reduces floating garbage and evacuationwork. Additionally, just as whole trains can be checked for the absenceof any references to their objects from locations outside those trains,subtrains can be, too, and a subtrain can thereby be recognized ascontaining only garbage in many cases in which the train to which itbelongs cannot.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention description below refers to the accompanying drawings, ofwhich:

FIG. 1, discussed above, is a block diagram of a computer system inwhich the present invention's teachings can be practiced;

FIG. 2 is, discussed above, is a block diagram that illustrates acompiler's basic functions;

FIG. 3, discussed above, is a block diagram that illustrates amore-complicated compiler/interpreter organization;

FIG. 4, discussed above, is a diagram that illustrates a basicgarbage-collection mechanism;

FIG. 5, discussed above, is a similar diagram illustrating thatgarbage-collection approach's relocation operation;

FIG. 6, discussed above, is a diagram that illustrates agarbage-collected heap's organization into generations;

FIG. 7, discussed above, is a diagram that illustrates a generationorganization employed for the train algorithm;

FIGS. 8A and 8B, discussed above, together constitute a flow chart thatillustrates a garbage-collection interval that includes old-generationcollection;

FIG. 9, discussed above, is a flow chart that illustrates in more detailthe remembered-set processing included in FIG. 8A;

FIG. 10, discussed above, is a block diagram that illustrates in moredetail the referred-to-object evacuation that FIG. 9 includes;

FIGS. 11A and 11B, discussed above, is a flow chart that illustrates inmore detail the FIG. 10 flow chart's step of processing evacuatedobjects' references;

FIGS. 12A–12J, discussed above, are diagrams that illustrate acollection scenario that can result from using the train algorithm;

FIGS. 13A and 13B together constitute a flow chart that illustrates acollection interval, as FIGS. 8A and 8B do, but illustratesoptimizations that FIGS. 8A and 8B do not include;

FIG. 14 is a flow chart of a routine for subdividing trains intosubtrains;

FIG. 15 is a data-structure diagram that depicts exemplary datastructures for supporting trains and cars;

FIG. 16 is a block diagram illustrating cars' train memberships thatprevail before a train has been subdivided;

FIG. 17 is a similar diagram showing the memberships as they exist afterthe train has been subdivided; and

FIG. 18 is a flow chart of a routine for moving an evacuated object to atrain in which a reference to it is located.

DETAILED DESCRIPTION OF AN ILLUSTRATIVE EMBODIMENT

The present invention's teachings of dividing trains into subtrains canbe practiced in essentially any implementation of the train algorithm.It can be employed in a train-algorithm-based collector that employs anoperational sequence essentially the same as that described above inconnection with FIGS. 8-11, for instance. But it can also be practicedin train-algorithm-based collectors that, for instance, spread acollection increment over a plurality of collection intervals instead ofconcentrating the whole collection increment in a single interval. Infact, as was mentioned above, train-algorithm-based collectors canperform some or all of the collection concurrently with mutatoroperation, and the present invention's teachings will be applicable tosuch collectors, too.

Even in collectors that concentrate an entire collection increment in asingle collection interval, moreover, the operational sequence candiffer significantly from that depicted in those drawings. For example,I prefer a sequence that FIGS. 13A and 13B (together, “FIG. 13”) depict.FIG. 13 corresponds to FIG. 8, but the operational sequence it depictsincludes some optimizations that I prefer to employ. And it shows aplace in the sequence where train subdividing may be performed.

Blocks 172, 176, and 178 represent operations that correspond to thosethat FIG. 8's blocks 102, 106, and 108 do, and dashed line 174represents the passage of control from the mutator to the collector, asFIG. 8's dashed line 104 does. As was mentioned above, embodiments ofthe present invention divide trains into subtrains. The particular pointin the sequence at which such subdividing occurs is not crucial. for thesake of example, though, FIG. 13 interposes block 179 between blocks 174and 176 to represent one possible point in the sequence at whichsubdividing can occur. One way of performing that subdividing will bedescribed in more detail after the discussion of the main sequence iscompleted.

For the sake of efficiency, the collection operation of FIG. 13 includesa step represented by block 180. In this step, the collector reads theremembered set of each car in the collection set to determine thelocation of each reference into the collection set from a car outside ofit, and it places the address of each reference thereby found into ascratch-pad list associated with the train that contains that reference.Some trains may be divided into subtrains and different scratch-padlists are associated with different subtrains of the same train. For thepurposes of this operation, therefore, the “train” that contains thereference may actually be a subtrain, in which case the scratch-pad listwill be a list associated with that subtrain. The collector places thescratch-pad lists in reverse-train order by subtrain, and, as blocks 182and 184 indicate, it then processes the entries in all scratch-pad listsbut the one associated with the oldest train (or, if that train has beensubdivided, all but those associated with the oldest train's subtrains).

Before the collector processes references in that train's scratch-padlist, the collector evacuates any objects referred to from outside theold generation, as block 186 indicates. To identify such objects, thecollector scans the root set. In some generational collectors, it mayalso have to scan other generations for references into the collectionset. For the sake of example, though, we have assumed the particularlycommon scheme in which a generation's collection in a given interval isalways preceded by complete collection of every (in this case, only one)younger generation in the same interval. If, in addition, thecollector's promotion policy is to promote all survivingyounger-generation objects into older generations, it is necessary onlyto scan older generations, of which there are none in the example; i.e.,some embodiments may not require that the young generation be scanned inthe block-186 operation.

For those that do, though, the scanning may actually involve inspectingeach surviving object in the young generation, or the collector mayexpedite the process by using card-table entries. Regardless of whichapproach it uses, the collector immediately evacuates into another trainany collection-set object to which it thereby finds an externalreference. The typical policy is to place the evacuated object into theyoungest such train. As before, the collector does not attempt toevacuate an object that has already been evacuated, and, when it doesevacuate an object to a train, it evacuates to the same train eachcollection set object to which a reference in the thus-evacuated objectrefers. In any case, the collector updates the reference to theevacuated object.

When the inter-generational references into the generation have thusbeen processed, the garbage collector determines whether there are anyreferences into the oldest train from outside that train. If not, theentire train can be reclaimed. Some embodiments may make thisdetermination not only for the oldest train but also for some youngertrains, at least if the oldest train turns out to be garbage. Even if noentire train cannot thereby be reclaimed, a large garbage structure maystill be recognized if the oldest train has been divided, as will beexplained in more detail below, into subtrains. If one of thosesubtrains includes no objects referred to from outside that subtrain,then the entire subtrain can be reclaimed. The collector may make thisdetermination for all of the oldest train's subtrains (and, in someembodiments, it may also do it for subtrains in some younger trains). Orit may make it for only the oldest subtrain, as the drawing's legendsuggests. Blocks 188 and 190 represents determining whether trains orsubtrains can be recognized as garbage and reclaiming them if they can.

As block 192 indicates, the collector interval typically ends when atrain has thus been collected. If the oldest train cannot be collectedin this manner, though, the collector proceeds to evacuate anycollection-set objects referred to by references whose locations theoldest train's scratch-pad list includes, as blocks 194 and 196indicate. It removes them to younger cars in the oldest train, againupdating references, avoiding duplicate evacuations, and evacuating anycollection-set objects to which the evacuated objects refer. When thisprocess has been completed, the collection set can be reclaimed, asblock 198 indicates, since no remaining object is referred to fromoutside the collection set: any remaining collection-set object isunreachable.

We now turn to the train-subdividing operation represented by FIG. 13A'sblock 179. FIG. 14 depicts an example routine that can be used for thispurpose. The particular order in which trains are considered forsubdividing is not critical, and block 202 merely represents selectingwhichever one is the first in the order that the collector uses for thispurpose. Block 204 represents determining whether the train meets thecollector's criterion for subdividing. Typically, the criterion issimply that the number of cars in the train has reached some thresholdvalue. For example, if the policy adopted by the collector is to have atarget subtrain size of between K and 2K cars, the threshold for trainsubdividing may be 2K cars: if a train has at least that many cars, thecollector divides it into two or more subtrains.

The specific steps taken to subdivide a train will beimplementation-dependent. For the sake of explanation, though, let ussuppose that the collector employs data structures similar to those thatFIG. 15 depicts. FIG. 15 depicts a train metadata structure 206 asincluding pointers 208 and 210 to the previous and next trains. This isone of the ways in which embodiments of the present invention may imposean order among the trains. Cars are ordered within trains, too, and itmay be convenient to assign numbers for this purpose explicitly and tohave a field 212 in the train structure store the next number to beassigned. In any event, some way of associating cars with trains isnecessary, and one way is for the train structure to include fields 214and 216 that point to metadata structures representing the train's firstand last cars.

FIG. 15 depicts one such car structure 218 as including pointers 220,222, and 224 to structures representing the train to which the carbelongs, the previous car in the train, and the next car in the train.Further pointers 226 and 228 point to the locations in the heap at whichthe associated car section begins and ends, whereas pointer 230 pointsto the place at which the next object can be added to the car section.

Now, the car that FIG. 15's data structure 218 represents willordinarily belong to a train that has not been subdivided. In theillustrated embodiment, the collector can recognize this by noting thata supertrain field 232 in the train structure 206 to which car 218'strain field 220 points does not contain a valid pointer to another trainstructure. Such a structure would represent a higher-level train ofwhich the train represented by structure 206 is a subtrain. If field 232contains NULL or some other value that does not point to a trainstructure, the train that structure 206 represents is not a subtrain.

FIG. 16 depicts a train structure 234 associated with a train that hasnot yet been subdivided. Cars 236, 238, 240, and 242 belong to thattrain. In FIG. 16, arrow 244 represents a first-car pointercorresponding to FIG. 15's pointer 214, and arrow 246 represents alast-car pointer corresponding to FIG. 15's pointer 216.

If the (atypically small) target subtrain size is two cars, enough carsbelong to FIG. 16's four-car train 234 to justify subdividing it. So,when the collector applies the test represented by FIG. 14's block 204to that train, the outcome is affirmative, and the collector createssubtrains for FIG. 16's train 234, as FIG. 14's block 248 indicates.

FIG. 17 depicts the result. The collector has allocated two furthertrain structures 250 and 252 to represent the subtrains, and first- andlast-subtrain pointers 254 and 256 corresponding to FIG. 15's fields 258and 260 are set to identify FIG. 17's sub-train structures 250 and 252.In train structures 250 and 252, the supertrain fields corresponding toFIG. 15's field 232 are set to identify FIG. 17's train structure 234.Additionally, train structure 250's next-train pointer 261 (FIG. 15'sfield 210) is set to point to the other subtrain structure 252, and thatstructure's previous-train pointer 262 (FIG. 15's field 208) is set topoint to structure 250.

As FIG. 14's block 263 indicates, the collector also assigns all oftrain 234's cars to subtrains 250 and 252. In cars 236 and 238, thetrain pointers, which correspond to FIG. 15's field 220, are set toidentify train 250 as the one to which they belong, whereas the trainpointers of cars 240 and 242 are set to identify train 252. Also, thesubtrains' first- and last-car pointers 264, 266, 268, and 270 areupdated appropriately.

As was mentioned above, the operation of FIG. 14 is typically, althoughnot necessarily, performed in connection with train numbering. If, asFIG. 15 indicates, the trains are organized in a linked list, thelinking imposes an implicit order on the trains. Typically, though, thecollector will assign each train a sequence number explicitly in orderto facilitate necessary comparisons during the collection operation.FIG. 15's train structure includes a field 272 for this purpose. Amongthe ways in which that numbering can be performed is the illustratedembodiment's approach of assigning numbers beginning with one for theoldest top-level train and incremented by one for each subsequenttop-level train. For subtrains, the numbering begins with one for thefirst subtrain in each higher-level train and continues until numbersare assigned to each subtrain in that train.

FIG. 14's blocks 274 and 276 indicate that, in the illustratedembodiment, the operation of considering the train for subdividing isrepeated for every train. But some embodiments may be more selectiveabout which trains they consider. In some embodiments, for instance, thecollector may consider only relatively young trains. Other embodimentsmay consider all trains but employ more-stringent criteria for sometrains than for others. Also, although FIG. 17 illustrates only a singlesubtrain level, some embodiments may apply the present invention'steachings to further levels.

Indeed, while the types of data structures depicted in FIG. 15 supportsuch multiple-level subdividing, simpler approaches may be used ifsubdividing is restricted to a single level. Rather than employ onetrain structure for a train and different structures for that train'ssubtrains, one could employ structures for the subtrains only, givingthem a common train number and linking them together in thetrain-and-subtrain sequence. Such an approach would dispense with FIG.15's supertrain field 232 and likely dispense with its fields 258 and260 for separately linking an individual train's subtrains.

Once the collector has thus subdivided trains into subtrains, it usesthe subtrains to determine which cars to use as destinations forevacuated objects. FIG. 18 is an example of a routine that can be usedfor doing so, i.e., for performing an operation corresponding to the onethat FIG. 10's block 126 represents. Basically, the collector evacuatesthe referred-to collection-set object to the last car in the reference'ssubtrain. Some embodiments will do this in all cases. But FIG. 18 givesan example of doing it only some of the time. Specifically, thatroutine's selection of the destination car to which the object is to beevacuated depends on whether the reference is located in a subtrain ofthe oldest train.

The FIG. 18 routine therefore begins, as block 280 indicates, bydetermining whether the train in which the reference is located is asubtrain. As was mentioned above, a collector that employs datastructures similar to those that FIG. 15 illustrates may follow carstructure 218's train pointer 220 to the train structure 206representing the train to which that reference belongs and then inspectthe contents of that train structure's supertrain pointer 232. If thatpointer's value is NULL or some other value for indicating the absenceof a supertrain, the collector concludes that the reference's train isnot a subtrain. As blocks 282 and 284 indicate, the collector thensimply proceeds normally: it places the referred-to object into the lastcar of the reference's train, i.e., into the train identified by thetrain pointer in the car structure representing the reference's carsection.

If the train pointer in that car structure identifies a train whosesupertrain field contains a valid train-structure address, on the otherhand, the outcome of the test represented by FIG. 18's block 280 isaffirmative: the reference's car section belongs to a subtrain. As wasindicated above, this ordinarily results in the referred-to object'sbeing placed in the last car of that subtrain, and, as FIG. 18's blocks286, 282, and 284 indicate, this is indeed the result if the subtrain isnot in the oldest train.

As blocks 286, 288, and 284 indicate, though, the illustrated embodimentevacuates the referred-to object to the last car in the oldest train'syoungest subtrain whenever the reference is located in a subtrain of theoldest train: the referred-to object does not necessarily end up in thesame subtrain as the reference that refers to it. Departing in thismanner from the general rule that the evacuated object is placed in thesame subtrain as the reference that referred to it compromises to someextent the invention's advantage of enhanced collocation. It alsoreduces to some extent the likelihood of finding that an entire subtrainis dead. So some embodiments may not make this oldest-train exception.

But others may adopt it on the theory that most of the collocationeffect will already have been obtained by evacuations into that train'ssubtrains before the train to which they belong became the oldest.

Conventionally, the occurrence of long trains containing long-livedobjects can adversely affect performance. Objects in long trains tend tobe placed a relatively long distance from the references that refer tothem. This lack of collocation increases the time it takes to collect anentire data structure. It also increases the number of times thatobjects need to be copied. Also, since it tends to make data structuresmore diffuse, their constituent objects tend not to be located asfrequently in the same cars, so they necessitate more remembered-setoperations. By breaking long trains into subtrains in accordance withthe present invention, a collector that employs the train algorithm canreduce these adverse effects significantly. The invention thusconstitutes a significant advance in the art.

1. For employing a computer system that includes memory to performgarbage collection in accordance with a train algorithm, a methodcomprising: A) treating a generation in the memory as divided into carsections organized into trains that have a front-to-rear order, at leastone train being divided into a plurality of subtrains such that each carbelonging to that train belongs to one subtrain thereof; and B)collecting the generation in accordance with the train algorithm incollection increments with which respective collection sets in thegeneration are associated, i) wherein in at least some of the collectionincrements: a) an object which is in a collection set and is referred toby references outside the collection set is evacuated to a given car ina train that has been divided into subtrains and contains thosereferences, only if the given car belongs to a subtrain that alsocontains a reference to that object; and b) the collection set isreclaimed; and ii) in each of at least some of which collectionincrements: a) a determination is made of whether any references locatedoutside the farthest-forward train refer to objects within that train;and b) each car section belonging to that train is reclaimed if thereare no such references.
 2. A method as defined in claim 1 that furtherincludes determining for at least one train whether a size of the trainhas reached a threshold and subdividing it into a plurality of subtrainsif it has.
 3. A method as defined in claim 1 that further includesdetermining for at least one train whether the number of cars in thetrain has reached a threshold and subdividing it into a plurality ofsubtrains if it has.
 4. A method as defined in claim 1 wherein everysubtrain to which an object referred to by a reference in the generationis evacuated contains a reference to that object if the subtrain is notpart of the farthest-forward train.
 5. A method as defined in claim 4wherein every subtrain to which an object referred to by a reference inthe generation is evacuated contains a reference to that object.
 6. Amethod as defined in claim 1 that, in at least some collectionincrements, includes: C) determining, for at least one subtrain, whetherany references located outside that subtrain refer to objects withinthat subtrain; and D) reclaiming each car section belonging to thatsubtrain if there are no such references.
 7. A computer system thatincludes memory and comprises: A) processor circuitry operable toexecute processor instructions; and B) memory circuitry, to which theprocessor circuitry is responsive, that contains processor instructionsreadable by the processor circuitry to configure the computer system tooperate as a garbage collector in accordance with a train algorithmthat: i) treats a generation in the memory as divided into car sectionsorganized into trains that have a front-to-rear order, at least onetrain being divided into a plurality of subtrains such that each carbelonging to that train belongs to one subtrain thereof; and ii)collects the generation in accordance with the train algorithm incollection increments with which respective collection sets in thegeneration are associated, a) wherein in at least some of the collectionincrements the garbage collector: (1) evacuates an object that is in acollection set and is referred to by references outside the collectionset to a given car in a train that has been divided into subtrains andcontains those references, only if the given car belongs to a subtrainthat also contains a reference to that object; and (2) reclaims thecollection set; and b) in each of at least some of which collectionincrements the garbage collector: (1) determines whether any referenceslocated outside the farthest-forward train refer to objects within thattrain; and (2) reclaims each car section belonging to that train ifthere are no such references.
 8. A computer system as defined in claim 7wherein the garbage collector determines for at least one train whethera size of the train has reached a threshold and subdivides it into aplurality of subtrains if it has.
 9. A computer system as defined inclaim 7 wherein the garbage collector determines for at least one trainwhether the number of cars in the train has reached a threshold andsubdivides it into a plurality of subtrains if it has.
 10. A computersystem as defined in claim 7 wherein every subtrain to which an objectreferred to by a reference in the generation is evacuated contains areference to that object if the subtrain is not part of thefarthest-forward train.
 11. A computer system as defined in claim 10wherein every subtrain to which an object referred to by a reference inthe generation is evacuated contains a reference to that object.
 12. Acomputer system as defined in claim 7 wherein, in at least somecollection increments, the garbage collector: C) determines, for atleast one subtrain, whether any references located outside that subtrainrefer to objects within that subtrain; and D) reclaims each car sectionbelonging to that subtrain if there are no such references.
 13. Astorage medium containing instructions readable by a computer system toconfigure the computer system to operate as a garbage collector inaccordance with a train algorithm that: A) treats a generation in thememory as divided into car sections organized into trains that have afront-to-rear order, at least one train being divided into a pluralityof subtrains such that each car belonging to that train belongs to onesubtrain thereof; and B) collects the generation in accordance with thetrain algorithm in collection increments with which respectivecollection sets in the generation are associated, i) wherein in at leastsome of the collection increments the garbage collector: a) evacuates anobject that is in a collection set and is referred to by referencesoutside the collection set to a given car in a train that is dividedinto subtrains and contains those references, only if the given carbelongs to a subtrain that also contains a reference to that object; andb) reclaims the collection set; and ii) in each of at least some ofwhich collection increments the garbage collector: a) determines whetherany references located outside the farthest-forward train refer toobjects within that train; and b) reclaims each car section belonging tothat train if there are no such references.
 14. A storage medium asdefined in claim 13 wherein the garbage collector determines for atleast one train whether a size of the train has reached a threshold andsubdivides it into a plurality of subtrains if it has.
 15. A storagemedium as defined in claim 13 wherein the garbage collector furtherdetermines for at least one train whether the number of cars in thetrain has reached a threshold and subdivides it into a plurality ofsubtrains if it has.
 16. A storage medium defined in claim 13 whereinevery subtrain to which an object referred to by a reference in thegeneration is evacuated contains a reference to that object if thesubtrain is not part of the farthest-forward train.
 17. A storage mediumas defined in claim 16 wherein every subtrain to which an objectreferred to by a reference in the generation is evacuated contains areference to that object.
 18. A storage medium as defined in claim 13wherein, in at least some collection increments, the garbage collector:C) determines, for at least one subtrain, whether any references locatedoutside that subtrain refer to objects within that subtrain; and D)reclaims each car section belonging to that subtrain if there are nosuch references.
 19. A garbage collector operating in the memory of acomputer and comprising: A) means for treating a generation in thememory as divided into car sections organized into trains that have afront-to-rear order, at least one train being divided into a pluralityof subtrains such that each car belonging to that train belongs to onesubtrain thereof; and B) means for collecting the generation inaccordance with a train algorithm in collection increments with whichrespective collection sets in the generation are associated, i) whereinin at least some of the collection increments: a) an object which is ina collection set and is referred to by references outside the collectionset is evacuated to a given car in a train that has been divided intosubtrains and contains those references, only if the given car belongsto a subtrain that also contains a reference to that object; and b) thecollection set is reclaimed; and ii) in each of at least some of whichcollection increments: a) a determination is made of whether anyreferences located outside the farthest-forward train refer to objectswithin that train; and b) each car section belonging to that train isreclaimed if there are no such references.